Target Audience

The potential candidates for the Amazon AWS Certified Data Analytics – Specialty exam are those individuals who are performing the Data Analytics roles. The test is generally targeted at the applicants who are working in different positions, such as a Solutions Architect, a Data Platform Engineer, a Data Scientist, as well as a Data Architect and a Data Analyst.

2. Data Analytics Fundamentals Digital Course by AWS Training

This is a digital training that is self-paced and allows candidates to learn more about planning data analysis solutions & processes. This course walks individuals through the five subjects of the AWS Certified Data Analytics exam, covering basic architecture, potential use cases, and value prepositions, among the rest. It provides detailed information about the AWS services and will the most beneficial for data scientists, data analysts, and data architects who want to enhance their skills in AWS solutions and their implementation. Some of the skills one will master during this program include the following:

• Classifying the characteristics of data analysis solutions
• Discovering different concepts of data schemas and defining how data and information is stored in the metastores
• Analyzing how Amazon EMR, Amazon Redshift, and AWS Glue work to process, transform, and cleanse data in data analysis solutions
• Knowledge of the types of data such as structured, unstructured, and semi-structured
• Understanding different ways used to analyze data and make reports with Amazon Athena and Amazon QuickSight tools
• Analyzing the characteristics of the storage system for source data
• Explain AWS services and their work to visualize data
• The use of Amazon Kinesis for processing streaming data

It is recommended to take this course after experiencing database concepts. The applicant should have a basic understanding of data storage, analytics, and processing. Sessions are offered in Japanese, Portuguese, Spanish, Indonesian, Thai, Vietnamese, Korean, Simplified Chinese, and English.

Reference: https://d1.awsstatic.com/training-and-certification/docs-data-analytics-specialty/AWS-Certified-Data-Analytics-Specialty-Exam-Guide_v1.0_08-23-2019_FINAL.pdf

Exam Topics

As for Amazon DAS-C01, the vendor provides the learners with the guide that includes the detailed information about all its domains. All in all, the topics covered in the exam content are as follows:

• Analysis and Visualization

  This topic is all about the students’ ability to demonstrate a wide range of technical tasks related to visualization and analysis of data, including selecting the right data visualization & data analysis solutions for a specific scenario, as well as determining the operational features of visualization and analysis solution.

• Processing

  In the framework of this subject area, the test takers have to perform their knowledge and skills in determining the proper data processing solution requirements, operationalizing & automating a data processing solution, designing a solution for preparing and transforming data for analysis, and more.

• Storage and Data Management

  This domain evaluates the professionals’ skills in determining the operational characteristics of the given storage solution for analytics, defining a data lifecycle based on the business requirements & usage patterns, determining an appropriate system for managing Metadata and cataloging data, as well as selecting the appropriate data layout, format, structure & schema, and determining data access & retrieval patterns.

• Collection

  The first part requires that the candidates demonstrate their expertise in determining the operational characteristics of features of the collection system, selecting a collection system that addresses the main properties of data, such as compression, format, and order, as well as selecting a collection system, which handles the source, volume, and frequency of data.

• Security

  The questions of the last objective are dedicated to validating the individuals’ understanding of selecting the appropriate authorization and authentication mechanisms, applying data compliance & governance controls, and applying data encryption & protection techniques.

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